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PURPOSE - To develop and investigate a set of biophysical models based on a mechanically coupled reaction-diffusion model of the spatiotemporal evolution of tumor growth after radiation therapy.
METHODS AND MATERIALS - Post-radiation therapy response is modeled using a cell death model (M), a reduced proliferation rate model (M), and cell death and reduced proliferation model (M). To evaluate each model, rats (n = 12) with C6 gliomas were imaged with diffusion-weighted magnetic resonance imaging (MRI) and contrast-enhanced MRI at 7 time points over 2 weeks. Rats received either 20 or 40 Gy between the third and fourth imaging time point. Diffusion-weighted MRI was used to estimate tumor cell number within enhancing regions in contrast-enhanced MRI data. Each model was fit to the spatiotemporal evolution of tumor cell number from time point 1 to time point 5 to estimate model parameters. The estimated model parameters were then used to predict tumor growth at the final 2 imaging time points. The model prediction was evaluated by calculating the error in tumor volume estimates, average surface distance, and voxel-based cell number.
RESULTS - For both the rats treated with either 20 or 40 Gy, significantly lower error in tumor volume, average surface distance, and voxel-based cell number was observed for the M and M models compared with the M model. The M model fit, however, had significantly lower sum squared error compared with the M and M models.
CONCLUSIONS - The results of this study indicate that for both doses, the M and M models result in accurate predictions of tumor growth, whereas the M model poorly describes response to radiation therapy.
Copyright © 2017 Elsevier Inc. All rights reserved.
Biophysical models designed to predict the growth and response of tumors to treatment have the potential to become a valuable tool for clinicians in care of cancer patients. Specifically, individualized tumor forecasts could be used to predict response or resistance early in the course of treatment, thereby providing an opportunity for treatment selection or adaption. This chapter discusses an experimental and modeling framework in which noninvasive imaging data is used to initialize and parameterize a subject-specific model of tumor growth. This modeling approach is applied to an analysis of murine models of glioma growth.
Although the functionality of the lens water channels aquaporin 1 (AQP1; epithelium) and AQP0 (fiber cells) is well established, less is known about the role of AQP5 in the lens. Since in other tissues AQP5 functions as a regulated water channel with a water permeability (P) some 20 times higher than AQP0, AQP5 could function to modulate P in lens fiber cells. To test this possibility, a fluorescence dye dilution assay was used to calculate the relative P of epithelial cells and fiber membrane vesicles isolated from either the mouse or rat lens, in the absence and presence of HgCl, an inhibitor of AQP1 and AQP5. Immunolabeling of lens sections and fiber membrane vesicles from mouse and rat lenses revealed differences in the subcellular distributions of AQP5 in the outer cortex between species, with AQP5 being predominantly membranous in the mouse but predominantly cytoplasmic in the rat. In contrast, AQP0 labeling was always membranous in both species. This species-specific heterogeneity in AQP5 membrane localization was mirrored in measurements of P, with only fiber membrane vesicles isolated from the mouse lens, exhibiting a significant Hg-sensitive contribution to P. When rat lenses were first organ cultured, immunolabeling revealed an insertion of AQP5 into cortical fiber cells, and a significant increase in Hg-sensitive P was detected in membrane vesicles. Our results show that AQP5 forms functional water channels in the rodent lens, and they suggest that dynamic membrane insertion of AQP5 may regulate water fluxes in the lens by modulating P in the outer cortex.
The choroid plexus epithelium (CPE) secretes higher volumes of fluid (cerebrospinal fluid, CSF) than any other epithelium and simultaneously functions as the blood-CSF barrier to gate immune cell entry into the central nervous system. Posthemorrhagic hydrocephalus (PHH), an expansion of the cerebral ventricles due to CSF accumulation following intraventricular hemorrhage (IVH), is a common disease usually treated by suboptimal CSF shunting techniques. PHH is classically attributed to primary impairments in CSF reabsorption, but little experimental evidence supports this concept. In contrast, the potential contribution of CSF secretion to PHH has received little attention. In a rat model of PHH, we demonstrate that IVH causes a Toll-like receptor 4 (TLR4)- and NF-κB-dependent inflammatory response in the CPE that is associated with a ∼3-fold increase in bumetanide-sensitive CSF secretion. IVH-induced hypersecretion of CSF is mediated by TLR4-dependent activation of the Ste20-type stress kinase SPAK, which binds, phosphorylates, and stimulates the NKCC1 co-transporter at the CPE apical membrane. Genetic depletion of TLR4 or SPAK normalizes hyperactive CSF secretion rates and reduces PHH symptoms, as does treatment with drugs that antagonize TLR4-NF-κB signaling or the SPAK-NKCC1 co-transporter complex. These data uncover a previously unrecognized contribution of CSF hypersecretion to the pathogenesis of PHH, demonstrate a new role for TLRs in regulation of the internal brain milieu, and identify a kinase-regulated mechanism of CSF secretion that could be targeted by repurposed US Food and Drug Administration (FDA)-approved drugs to treat hydrocephalus.
Alveolar macrophages (AMs) are multitasking cells that maintain lung homeostasis by clearing apoptotic cells (efferocytosis) and performing antimicrobial effector functions. Different PRRs have been described to be involved in the binding and capture of non-opsonized Streptococcus pneumoniae, such as TLR-2, mannose receptor (MR) and scavenger receptors (SRs). However, the mechanism by which the ingestion of apoptotic cells negatively influences the clearance of non-opsonized S. pneumoniae remains to be determined. In this study, we evaluated whether the prostaglandin E2 (PGE) produced during efferocytosis by AMs inhibits the ingestion and killing of non-opsonized S. pneumoniae. Resident AMs were pre-treated with an E prostanoid (EP) receptor antagonist, inhibitors of cyclooxygenase and protein kinase A (PKA), incubated with apoptotic Jurkat T cells, and then challenged with S. pneumoniae. Efferocytosis slightly decreased the phagocytosis of S. pneumoniae but greatly inhibited bacterial killing by AMs in a manner dependent on PGE production, activation of the EP2-EP4/cAMP/PKA pathway and inhibition of HO production. Our data suggest that the PGE produced by AMs during efferocytosis inhibits HO production and impairs the efficient clearance non-opsonized S. pneumoniae by EP2-EP4/cAMP/PKA pathway.
While gliomas have been extensively modelled with a reaction-diffusion (RD) type equation it is most likely an oversimplification. In this study, three mathematical models of glioma growth are developed and systematically investigated to establish a framework for accurate prediction of changes in tumour volume as well as intra-tumoural heterogeneity. Tumour cell movement was described by coupling movement to tissue stress, leading to a mechanically coupled (MC) RD model. Intra-tumour heterogeneity was described by including a voxel-specific carrying capacity (CC) to the RD model. The MC and CC models were also combined in a third model. To evaluate these models, rats ( = 14) with C6 gliomas were imaged with diffusion-weighted magnetic resonance imaging over 10 days to estimate tumour cellularity. Model parameters were estimated from the first three imaging time points and then used to predict tumour growth at the remaining time points which were then directly compared to experimental data. The results in this work demonstrate that mechanical-biological effects are a necessary component of brain tissue tumour modelling efforts. The results are suggestive that a variable tissue carrying capacity is a needed model component to capture tumour heterogeneity. Lastly, the results advocate the need for additional effort towards capturing tumour-to-tissue infiltration.
© 2017 The Author(s).
Inhibitors of the renin-angiotensin system used to treat several diseases have also been shown to be effective on bone tissue, suggesting that angiotensin-converting enzyme inhibitors and angiotensin receptor blockers may reduce fracture risk. The present study investigated the effects of losartan on the physicochemical and biomechanical properties of diabetic rat bone. Losartan (5 mg/kg/day) was administered via oral gavage for 12 weeks. Bone mineral density (BMD) was measured using dual-energy X-ray absorptiometry. Whole femurs were tested under tension to evaluate the biomechanical properties of bone. The physicochemical properties of bone were analyzed by Fourier transform infrared spectroscopy. Although losartan did not recover decreases in the BMD of diabetic bone, it recovered the physicochemical (mineral and collagen matrix) properties of diabetic rat bone. Furthermore, losartan also recovered ultimate tensile strength of diabetic rat femurs. Losartan, an angiotensin II type 1 receptor blocker, has a therapeutic effect on the physicochemical properties of diabetic bone resulting in improvement of bone strength at the material level. Therefore, specific inhibition of this pathway at the receptor level shows potential as a therapeutic target for diabetic patients suffering from bone diseases such as osteopenia.
BACKGROUND AND OBJECTIVE - LP533401 is an inhibitor of tryptophan hydroxylase 1, which regulates serotonin production in the gut. Previous work indicates that LP533401 has an anabolic effect in bone. Thus, we hypothesized that inhibition of gut serotonin production may modulate the host response in periodontal disease. In this study, we aimed to analyze the effects of LP533401 in a rat periodontitis model to evaluate the role of gut serotonin in periodontitis pathophysiology.
MATERIAL AND METHODS - Twenty-four rats were divided into three groups: treated group (T: ligature-induced periodontal disease and LP533401, 25 mg/kg/d) by gavage; ligature group (L: ligature-induced periodontal disease only); and control group (C: without ligature-induced periodontal disease). After 28 d, radiographic alveolar bone support was measured on digital radiographs, and alveolar bone volume fraction, tissue mineral density and trabeculae characteristics were quantified by microcomputed tomography in the right hemi-mandible. Left hemi-mandibles were decalcified and alveolar bone loss, attachment loss and area of collagen in the gingiva were histologically analyzed.
RESULTS - Significant difference between the L and C groups was found, confirming that periodontal disease was induced. We observed no difference between the T and L groups regarding alveolar bone destruction and area of collagen.
CONCLUSION - LP533401 (25 mg/kg/d) for 28 d does not prevent bone loss and does not modulate host response in a rat model of induced periodontal disease.
© 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
Mitochondria are critical for respiration in all tissues; however, in liver, these organelles also accommodate high-capacity anaplerotic/cataplerotic pathways that are essential to gluconeogenesis and other biosynthetic activities. During nonalcoholic fatty liver disease (NAFLD), mitochondria also produce ROS that damage hepatocytes, trigger inflammation, and contribute to insulin resistance. Here, we provide several lines of evidence indicating that induction of biosynthesis through hepatic anaplerotic/cataplerotic pathways is energetically backed by elevated oxidative metabolism and hence contributes to oxidative stress and inflammation during NAFLD. First, in murine livers, elevation of fatty acid delivery not only induced oxidative metabolism, but also amplified anaplerosis/cataplerosis and caused a proportional rise in oxidative stress and inflammation. Second, loss of anaplerosis/cataplerosis via genetic knockdown of phosphoenolpyruvate carboxykinase 1 (Pck1) prevented fatty acid-induced rise in oxidative flux, oxidative stress, and inflammation. Flux appeared to be regulated by redox state, energy charge, and metabolite concentration, which may also amplify antioxidant pathways. Third, preventing elevated oxidative metabolism with metformin also normalized hepatic anaplerosis/cataplerosis and reduced markers of inflammation. Finally, independent histological grades in human NAFLD biopsies were proportional to oxidative flux. Thus, hepatic oxidative stress and inflammation are associated with elevated oxidative metabolism during an obesogenic diet, and this link may be provoked by increased work through anabolic pathways.
Reaction-diffusion models have been widely used to model glioma growth. However, it has not been shown how accurately this model can predict future tumor status using model parameters (i.e., tumor cell diffusion and proliferation) estimated from quantitative in vivo imaging data. To this end, we used in silico studies to develop the methods needed to accurately estimate tumor specific reaction-diffusion model parameters, and then tested the accuracy with which these parameters can predict future growth. The analogous study was then performed in a murine model of glioma growth. The parameter estimation approach was tested using an in silico tumor 'grown' for ten days as dictated by the reaction-diffusion equation. Parameters were estimated from early time points and used to predict subsequent growth. Prediction accuracy was assessed at global (total volume and Dice value) and local (concordance correlation coefficient, CCC) levels. Guided by the in silico study, rats (n = 9) with C6 gliomas, imaged with diffusion weighted magnetic resonance imaging, were used to evaluate the model's accuracy for predicting in vivo tumor growth. The in silico study resulted in low global (tumor volume error <8.8%, Dice >0.92) and local (CCC values >0.80) level errors for predictions up to six days into the future. The in vivo study showed higher global (tumor volume error >11.7%, Dice <0.81) and higher local (CCC <0.33) level errors over the same time period. The in silico study shows that model parameters can be accurately estimated and used to accurately predict future tumor growth at both the global and local scale. However, the poor predictive accuracy in the experimental study suggests the reaction-diffusion equation is an incomplete description of in vivo C6 glioma biology and may require further modeling of intra-tumor interactions including segmentation of (for example) proliferative and necrotic regions.